multibias: Simultaneous Multi-Bias Adjustment

Quantify the causal effect of a binary exposure on a binary outcome with adjustment for multiple biases. The functions can simultaneously adjust for any combination of uncontrolled confounding, exposure/outcome misclassification, and selection bias. The underlying method generalizes the concept of combining inverse probability of selection weighting with predictive value weighting. Simultaneous multi-bias analysis can be used to enhance the validity and transparency of real-world evidence obtained from observational, longitudinal studies. Based on the work from Paul Brendel, Aracelis Torres, and Onyebuchi Arah (2023) <doi:10.1093/ije/dyad001>.

Version:	1.4.0
Depends:	R (≥ 2.10)
Imports:	dplyr (≥ 1.1.3), magrittr (≥ 2.0.3), rlang (≥ 1.1.1)
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2024-01-27
Author:	Paul Brendel [aut, cre, cph]
Maintainer:	Paul Brendel <pcbrendel at gmail.com>
BugReports:	https://github.com/pcbrendel/multibias/issues
License:	MIT + file LICENSE
URL:	https://github.com/pcbrendel/multibias
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	multibias results

Documentation:

Reference manual:	multibias.pdf
Vignettes:	Multi-Bias Examples

Downloads:

Package source:	multibias_1.4.0.tar.gz
Windows binaries:	r-devel: multibias_1.4.0.zip, r-release: multibias_1.4.0.zip, r-oldrel: multibias_1.4.0.zip
macOS binaries:	r-release (arm64): multibias_1.4.0.tgz, r-oldrel (arm64): multibias_1.4.0.tgz, r-release (x86_64): multibias_1.4.0.tgz, r-oldrel (x86_64): multibias_1.4.0.tgz
Old sources:	multibias archive

Linking:

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